Ultrasonography of vulnerable atherosclerotic plaque in the carotid arteries: B-mode imaging

Novel imaging modalities for the identification of vulnerable plaques

Atherosclerosis is a slow, progressive disease that is closely associated with major adverse cardiovascular events. Early diagnosis and risk assessment of atherosclerosis can effectively improve the prognosis and reduce the occurrence of adverse cardiovascular events in the later stage. A variety of invasive and non-invasive imaging modalities are important tools for diagnosing lesions, monitoring the efficacy of treatments, and predicting associated risk events. This review mainly introduces the four commonly used non-invasive imaging modalities in clinical practice and intravascular imaging such as optical coherence tomography, intravascular ultrasound imaging, and near-infrared spectroscopy, compares the advantages and disadvantages in the diagnosis of vulnerable plaques, and briefly summarizes the new progressions of each.

Advancements in risk stratification and management strategies in primary cardiovascular prevention

Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of morbidity and mortality worldwide, highlighting the urgent need for advancements in risk assessment and management strategies. Although significant progress has been made recently, identifying and managing apparently healthy individuals at a higher risk of developing atherosclerosis and those with subclinical atherosclerosis still poses significant challenges. Traditional risk assessment tools have limitations in accurately predicting future events and fail to encompass the complexity of the atherosclerosis trajectory. In this review, we describe novel approaches in biomarkers, genetics, advanced imaging techniques, and artificial intelligence that have emerged to address this gap. Moreover, polygenic risk scores and imaging modalities such as coronary artery calcium scoring, and coronary computed tomography angiography offer promising avenues for enhancing primary cardiovascular risk stratification and personalised intervention strategies. On the other hand, interventions aiming against atherosclerosis development or promoting plaque regression have gained attention in primary ASCVD prevention. Therefore, the potential role of drugs like statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, omega-3 fatty acids, antihypertensive agents, as well as glucose-lowering and anti-inflammatory drugs are also discussed. Since findings regarding the efficacy of these interventions vary, further research is still required to elucidate their mechanisms of action, optimize treatment regimens, and determine their long-term effects on ASCVD outcomes. In conclusion, advancements in strategies addressing atherosclerosis prevention and plaque regression present promising avenues for enhancing primary ASCVD prevention through personalised approaches tailored to individual risk profiles. Nevertheless, ongoing research efforts are imperative to refine these strategies further and maximise their effectiveness in safeguarding cardiovascular health.

Optoacoustic biomarkers of lipids, hemorrhage and inflammation in carotid atherosclerosis

Imaging plays a critical role in exploring the pathophysiology and enabling the diagnostics and therapy assessment in carotid artery disease. Ultrasonography, computed tomography, magnetic resonance imaging and nuclear medicine techniques have been used to extract of known characteristics of plaque vulnerability, such as inflammation, intraplaque hemorrhage and high lipid content. Despite the plethora of available techniques, there is still a need for new modalities to better characterize the plaque and provide novel biomarkers that might help to detect the vulnerable plaque early enough and before a stroke occurs. Optoacoustics, by providing a multiscale characterization of the morphology and pathophysiology of the plaque could offer such an option. By visualizing endogenous (e.g., hemoglobin, lipids) and exogenous (e.g., injected dyes) chromophores, optoacoustic technologies have shown great capability in imaging lipids, hemoglobin and inflammation in different applications and settings. Herein, we provide an overview of the main optoacoustic systems and scales of detail that enable imaging of carotid plaques in vitro, in small animals and humans. Finally, we discuss the limitations of this novel set of techniques while investigating their potential to enable a deeper understanding of carotid plaque pathophysiology and possibly improve the diagnostics in future patients with carotid artery disease.

Impact of cerebral collateral flow on stroke outcomes after carotid stenting

OBJECTIVE

Internal carotid artery stenosis is a main contributor to recurrent ischemic stroke. This study aimed to evaluate associations between recurrent stroke and changes in prestenting flow direction in the primary collaterals or both primary and secondary collaterals, and the potential interaction between extra- and intracranial arteries.

METHODS

This longitudinal study recruited stroke patients without intracranial stenosis who underwent right-side carotid stenting between 2011 and 2019. The main study outcome was recurrent stroke. Predictive factors were anterior circulation flow direction change (ACFDC), posterior circulation flow direction change, and reversal of ophthalmic artery/leptomeningeal anastomosis (ROALA) detected by transcranial color-coded duplex (TCCD) before carotid stenting. Patient follow-up was 9 years. Risk factors for recurrent stroke were identified by Kaplan-Meier plot and Cox regression analyses.

RESULTS

A total of 234 patients (mean age 70.88 ± 10.3 years, 86.32% male) were included, and 115 had recurrent stroke. Kaplan-Meier plot showed that patients with left ACFDC and ROALA had worse outcomes than those with ACFDC only, while patients with left ACFDC had worse outcome than those with right ACFDC (both p < 0.001). Cox regression analysis showed that recurrent stoke was associated with ACFDC at right (hazard ratio [95% CI]: 20.988 [2.549-172.790], p < 0.01), left (151.441 [20.100-1140.993], p < 0.001), and both sides (144.889 [19.089-1099.710], p < 0.001).

INTERPRETATION

Anterior circulation flow direction change is significantly associated with recurrent stroke in patients with unilateral carotid stenosis. Patients with ACFDC and ROALA together have worse outcomes compared to those with ACFDC only. Prestenting TCCD images help provide definitive information to predict outcomes after carotid stenting.

Contrast-Enhanced Ultrasound Feasibility in Assessing Carotid Plaque Vulnerability-Narrative Review

The risk assessment for carotid atherosclerotic lesions involves not only determining the degree of stenosis but also plaque morphology and its composition. Recently, carotid contrast-enhanced ultrasound (CEUS) has gained importance for evaluating vulnerable plaques. This review explores CEUS's utility in detecting carotid plaque surface irregularities and ulcerations as well as intraplaque neovascularization and its alignment with histology. Initial indications suggest that CEUS might have the potential to anticipate cerebrovascular incidents. Nevertheless, there is a need for extensive, multicenter prospective studies that explore the relationships between CEUS observations and patient clinical outcomes in cases of carotid atherosclerotic disease.

HViT: Hybrid vision inspired transformer for the assessment of carotid artery plaque by addressing the cross-modality domain adaptation problem in MRI

BACKGROUND

Medical image classification is crucial for accurate and efficient diagnosis, and deep learning frameworks have shown significant potential in this area. When a general learning deep model is directly deployed to a new dataset with heterogeneous features, the effect of domain shifts is usually ignored, which degrades the performance of deep learning models and leads to inaccurate predictions.

PURPOSE

This study aims to propose a framework that utilized the cross-modality domain adaptation and accurately diagnose and classify MRI scans and domain knowledge into stable and vulnerable plaque categories by a modified Vision Transformer (ViT) model for the classification of MRI scans and transformer model for domain knowledge classification.

METHODS

This study proposes a Hybrid Vision Inspired Transformer (HViT) framework that employs a convolutional layer for image pre-processing and normalization and a 3D convolutional layer to enable ViT to classify 3D images. Our proposed HViT framework introduces a slim design with a multi-branch network and channel attention, improving patch embedding extraction and information learning. Auxiliary losses target shallow features, linking them with deeper ones, enhancing information gain, and model generalization. Furthermore, replacing the MLP Head with RNN enables better backpropagation for improved performance. Moreover, we utilized a modified transformer model with LSTM positional encoding and Golve word vector to classify domain knowledge. By using ensemble learning techniques, specifically stacking ensemble learning with hard and soft prediction, we combine the predictive power of both models to address the cross-modality domain adaptation problem and improve overall performance.

RESULTS

The proposed framework achieved an accuracy of 94.32% for carotid artery plaque classification into stable and vulnerable plaque by addressing the cross-modality domain adaptation problem and improving overall performance.

CONCLUSION

The model was further evaluated using an independent dataset acquired from different hardware protocols. The results demonstrate that the proposed deep learning model significantly improves the generalization ability across different MRI scans acquired from different hardware protocols without requiring additional calibration data.

Novel Imaging-Based Biomarkers for Identifying Carotid Plaque Vulnerability

Carotid artery disease has traditionally been assessed based on the degree of luminal narrowing. However, this approach, which solely relies on carotid stenosis, is currently being questioned with regard to modern risk stratification approaches. Recent guidelines have introduced the concept of the "vulnerable plaque," emphasizing specific features such as thin fibrous caps, large lipid cores, intraplaque hemorrhage, plaque rupture, macrophage infiltration, and neovascularization. In this context, imaging-based biomarkers have emerged as valuable tools for identifying higher-risk patients. Non-invasive imaging modalities and intravascular techniques, including ultrasound, computed tomography, magnetic resonance imaging, intravascular ultrasound, optical coherence tomography, and near-infrared spectroscopy, have played pivotal roles in characterizing and detecting unstable carotid plaques. The aim of this review is to provide an overview of the evolving understanding of carotid artery disease and highlight the significance of imaging techniques in assessing plaque vulnerability and informing clinical decision-making.

Diagnostics of atherosclerosis: Overview of the existing methods

Atherosclerosis was and remains an extremely common and serious health problem. Since the elderly are most at risk of cardiovascular risk, and the average life expectancy is increasing, the spread of atherosclerosis and its consequences increases as well. One of the features of atherosclerosis is its asymptomaticity. This factor makes it difficult to make a timely diagnosis. This entails the lack of timely treatment and even prevention. To date, in the arsenal of physicians, there is only a limited set of methods to suspect and fully diagnose atherosclerosis. In this review, we have tried to briefly describe the most common and effective methods for diagnosing atherosclerosis.

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study

OBJECTIVES

Accurate detection of carotid plaque using ultrasound (US) is essential for preventing stroke. However, the diagnostic performance of junior radiologists (with approximately 1 year of experience in carotid US evaluation) is relatively poor. We thus aim to develop a deep learning (DL) model based on US videos to improve junior radiologists' performance in plaque detection.

METHODS

This multicenter prospective study was conducted at five hospitals. CaroNet-Dynamic automatically detected carotid plaque from carotid transverse US videos allowing clinical detection. Model performance was evaluated using expert annotations (with more than 10 years of experience in carotid US evaluation) as the ground truth. Model robustness was investigated on different plaque characteristics and US scanning systems. Furthermore, its clinical applicability was evaluated by comparing the junior radiologists' diagnoses with and without DL-model assistance.

RESULTS

A total of 1647 videos from 825 patients were evaluated. The DL model yielded high performance with sensitivities of 87.03% and 94.17%, specificities of 82.07% and 74.04%, and areas under the receiver operating characteristic curve of 0.845 and 0.841 on the internal and multicenter external test sets, respectively. Moreover, no significant difference in performance was noted among different plaque characteristics and scanning systems. Using the DL model, the performance of the junior radiologists improved significantly, especially in terms of sensitivity (largest increase from 46.3 to 94.44%).

CONCLUSIONS

The DL model based on US videos corresponding to real examinations showed robust performance for plaque detection and significantly improved the diagnostic performance of junior radiologists.

KEY POINTS

• The deep learning model based on US videos conforming to real examinations showed robust performance for plaque detection. • Computer-aided diagnosis can significantly improve the diagnostic performance of junior radiologists in clinical practice.

The utility of ultrasound and computed tomography in the assessment of carotid artery plaque vulnerability-A mini review

As the burden of cardiovascular and cerebrovascular events continues to increase, emerging evidence supports the concept of plaque vulnerability as a strong marker of plaque rupture, and embolization. Qualitative assessment of the plaque can identify the degree of plaque instability. Ultrasound and computed tomography (CT) have emerged as safe and accurate techniques for the assessment of plaque vulnerability. Plaque features including but not limited to surface ulceration, large lipid core, thin fibrous cap (FC), intraplaque neovascularization and hemorrhage can be assessed and are linked to plaque instability.

Advances in Noninvasive Carotid Wall Imaging with Ultrasound: A Narrative Review

Carotid atherosclerosis is a major cause for stroke, with significant associated disease burden morbidity and mortality in Western societies. Diagnosis, grading and follow-up of carotid atherosclerotic disease relies on imaging, specifically ultrasound (US) as the initial modality of choice. Traditionally, the degree of carotid lumen stenosis was considered the sole risk factor to predict brain ischemia. However, modern research has shown that a variety of other imaging biomarkers, such as plaque echogenicity, surface morphology, intraplaque neovascularization and vasa vasorum contribute to the risk for rupture of carotid atheromas with subsequent cerebrovascular events. Furthermore, the majority of embolic strokes of undetermined origin are probably arteriogenic and are associated with nonstenosing atheromas. Therefore, a state-of-the-art US scan of the carotid arteries should take advantage of recent technical developments and should provide detailed information about potential thrombogenic (/) and emboligenic arterial wall features. This manuscript reviews recent advances in ultrasonographic assessment of vulnerable carotid atherosclerotic plaques and highlights the fields of future development in multiparametric arterial wall imaging, in an attempt to convey the most important take-home messages for clinicians performing carotid ultrasound.

Carotid Plaque Composition and the Importance of Non-Invasive in Imaging Stroke Prevention

Luminal stenosis has been the standard feature for the current management strategies in patients with atherosclerotic carotid disease. Histological and imaging studies show considerable differences between plaques with identical degrees of stenosis. They indicate that specific plaque characteristics like Intraplaque hemorrhage, Lipid Rich Necrotic Core, Plaque Inflammation, Thickness and Ulceration are responsible for the increased risk of ischemic events. Intraplaque hemorrhage is defined by the accumulation of blood components within the plaque, Lipid Rich Necrotic Core is composed of macrophages loaded with lipid, Plaque Inflammation is defined as the process of atherosclerosis itself and Plaque thickness and Ulceration are defined as morphological features. Advances in imaging methods like Magnetic Resonance Imaging, Ultrasound, Computed Tomography and Positron Emission Tomography have enabled a more detailed characterization of the plaque, and its vulnerability is linked to these characteristics, changing the management of these patients based only on the degree of plaque stenosis. Studies like Rotterdam, ARIC, PARISK, CAPIAS and BIOVASC were essential to evaluate and prove the relevance of these characteristics with cerebrovascular symptoms. A better approach for the prevention of stroke is needed. This review summarizes the more frequent carotid plaque features and the available validation from recent studies with the latest evidence.